Advanced AI based Controller for Wind Turbine Pitch Control

Wind Turbine (WT) systems actively contribute to frequency and voltage stability, making them an essential component of modern power generation. WT output may be maximized by considering elements such as wind speed and blade pitch angle. However, when it comes to making maximum wind energy, the pitch angle is critical because the wind speed is variable and varies on the topographical circumstances of the various locations. Because the amount of energy taken is restricted by Betz Law, it is evident that using pitch angle controllers, itis feasible to achieve the desired result for certain circumstances. As a result, a well-designed pitch angle controller is essential for achieving better performance. The nonlinearities, complex dynamics, interconnected variables, and environmental uncertainty make WT pitch control a difficult task to solve. Techniques to control WT’s pitch based on Artificial Intelligence (AI) are emerging as a viable solution to these challenges. The purpose of the AI controller developed here is to regulate the WT’s pitch angle. Transfer function notation is used to describe the mathematical model of the WT. Following that, an AI controller is created, and its performance is compared to that of a regular Proportional Integral Derivative (PID) controller. For comparison, time response and error metrics such as Mean Square Error (MSE) and Mean Absolute Error (MAE) are employed. From this comparison, it can be seen that the AI controller gives adequate solutions to the set point tracking and disturbance rejection challenges.